Business Analytics Certificate Program | Northwestern SPS - Northwestern School of Professional Studies

Data and analytics are fundamental in the solving of business and organizational problems. Mastering these practices requires a well-rounded introduction, regardless of whether you are performing the analysis or implementing the results. Introduction to Business Analytics provides a solid foundation by beginning with basic principles in data modeling and intelligent information. We then continue with how to define business goals, various techniques for collecting and preparing data, different types of analysis and predictive models, and effective ways of communicating results.

The course will discuss many of the latest technology trends applicable to big data and predictive analytics, and includes examples from real use cases to provide a comprehensive, innovative, and practical approach to tackle business analytics problems. Students will also learn strategies to successfully approach stakeholders within an organization with analytic information while navigating the ethical, regulatory, and compliance issues related to the use of data analytics.

Content / Topics

Analytics Terminology, Methodology and Tools (with Statistical Concepts)
Descriptive, Prescriptive, and Predictive Analytics
Business Intelligence vs Business Analytics
Data Collection, Sampling, Preprocessing, Typing, and Governance
Designing a Data Analytics Study
Analytics Project Lifecycle
Implementation / Application of Business Analytics
Latest Analytical Technologies

Registered students can access their online course site here. An activated NetID and password is required for login. *Please note: It may take up to 24-hours for registered students to be added to the online course platform.

Modeling Concepts for Business Analytics is tailored to the needs of non-practitioners who interact with statisticians and data scientists, including managers, technology partners, and business users. We will present the basic statistical and machine learning techniques that are used by data scientists to analyze and model data, but will not spend time on the intricate details of each model or how they are coded. Instead, students will learn the basics of each technique with an emphasis on understanding what the algorithm does, what it is used for, and the pros and cons of each. We will also cover best practices for managers and information technology professionals who are upstream or downstream from the analysts.

Course Objectives

By the end of this course, students will be able to:

• Describe applications of key data mining methods for business decision-making.
• Articulate data mining terminology.
• Explain what to look for when evaluating various data mining methods.
• Interpret results from various data mining methods.
• Communicate methods and strategies with internal or external business data stakeholders.

Prerequisites

Students must complete BUS_ANLY 201-DL before registering for this course.

Registered students can access their online course site here. An activated NetID and password is required for login. *Please note: It may take up to 24-hours for registered students to be added to the online course platform.

This course is designed to empower professionals with the skills to integrate business analytics into their organization’s decision-making processes, enhancing competitive advantage and value creation. Tailored for individuals who are not data scientists but need to effectively consume and communicate data and analytics, this course covers essential topics including promoting analytical thinking, building consensus, and adopting smart metrics for project development, implementation, evaluation, and monitoring.

A strong emphasis is placed on the visual display of data and the effective communication of complex analytical results to diverse audiences, including clients, staff, non-technical leaders, and senior management. Participants will explore various dashboarding and graphics technologies and will work with real-world examples from industries such as finance, healthcare, retail, government, marketing, and sales.

Students will gain hands-on experience in making the case for analytics, presenting their findings, and demonstrating the added value and competitive edge derived from their insights. Each student will receive a 3-month license for Tableau, the leading platform for data exploration and management, featuring generative AI capabilities for accelerated value and reduced repetitive tasks. Upon expiration, the license can be renewed at the student rate for an additional year.

Course Objectives

By the end of this course, students will be able to:

• Formulate data profiles and generate thoughtful actionable insights.
• Summarize complex analytical results into simple, encompassing, and convincing visual analytics.
• Create presentations for delivery to a mixed technical and non-technical audience.
• Create effective visualizations using best practices and synthesize them into illuminating stories.
• Illustrate the comprehension of data storytelling through the sharing of a video story with the class.

Advanced Modeling Methods gives business analysts the foundation and tools to implement various prediction algorithms that will allow them to make better data driven decision for their business. This course places emphasis on modeling techniques to gain insight into hidden data patterns while using the technology stack of R. Topics covered will include various classification algorithms such as Cluster Analysis, Neural Networks, Discriminant Analysis, and Support Vector Machines. Students will also be introduced to various topics in Time Series, and other statistical based methods including Principal Component Analysis and Affinity Analysis. Lastly, students will learn about the structure of Networks and how tools such as Sentiment Analysis can provide valuable insight into their customer base.

PREREQUISITES: Students must complete BUS_ANLY 201 and BUS_ANLY 202 before registering for this course.

Registered students can access their online course site here. An activated NetID and password is required for login. *Please note: It may take up to 24-hours for registered students to be added to the online course platform.